BOHR International Journal of Internet of things, Artificial Intelligence and Machine Learning (BIJIAM) is an open access peer-reviewed journal that publishes articles which contribute new results in all the areas of Internet of things, Artificial Intelligence and Machine Learning. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in this area.
Published: 2022-12-14
Methods
Robotic Mushroom Harvesting by Employing Probabilistic Road Map and Inverse Kinematics
Article Type : Methods
DOI: 10.54646/bijiam.2022.011–11
Implementation of Decentralized Techniques in E-Commerce Website
Article Type : Methods
DOI: 10.54646/bijiam.2022.0212-14
Deep Learning Analysis for Estimating Sleep Syndrome Detection Utilizing the Twin Convolutional Model FTC2
Article Type : Methods
DOI: 10.54646/bijiam.2022.0315-21
Transforming African Education Systems through the Application of IOT
Article Type : Methods
DOI: 10.54646/bijiam.2022.0422-24
Automation Attendance Systems Approaches: A Practical Review
Article Type : Methods
DOI: 10.54646/bijiam.2022.0525-34
Evaluation of Sustainability of Using Autonomous Vehicles for the Last-Mile Delivery Industry
Article Type : Methods
DOI: 10.54646/bijiam.2022.0635-46
An Internet of Things Enabled Smart Firefighting System
Article Type : Methods
DOI: 10.54646/bijiam.2022.0747-51
Role of Artificial Intelligence in Supply Chain Management
Article Type : Methods
DOI: 10.54646/bijiam.2022.0852-55
Hybrid Facial Expression Recognition (FER2013) Model for Real-Time Emotion Classification and Prediction
Article Type : Methods
DOI: 10.54646/bijiam.2022.0956-64
Enhanced 3D Brain Tumor Segmentation Using Assorted Precision Training
Article Type : Methods
DOI: 10.54646/bijiam.2022.1065-69